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Phasing out coal-fired power plants is one of the most urgent steps needed to achieve the 1.5- or 2-degree target in the Paris Agreement. Many developed and developing countries have announced their plans to phase out coal from their electricity sectors. Managing the social and economic impacts of this energy transition is key to achieving political and social acceptability and pursuing environmental and social development hand in hand. As one of the leading countries committed to decarbonization in Latin America, Chile has launched a plan to phase out coal by 2050. To analyze the impacts of phasing out coal in Chile on jobs and value added, we combined an Input-Output analysis with ad-hoc labor surveys. We analyzed four contrasting electricity production scenarios that the Chilean government used to frame the policy debate: the current Long-Term Energy Plan (a baseline), and three scenarios that phase out coal-based generation by 2030 or 2050. Our findings show that coal phase-out will contribute to net job creation on the national level, adding 23–26 thousand jobs by 2030. In addition, value-added in the power generation sector will also grow by 1.7 billion dollars above today's levels as a result of the coal phase-out. These overall positive numbers mask a gross job destruction of 4.4 thousand jobs in coal power plants, concentrated in a few communities. In the most affected community, 7.1% of the population works in a coal power plant. Negative impacts in coal-reliant communities require special attention to ensure a just transition towards a clean power generation system. The results of this study highlight the need for strategic policy development that supports a smooth transition to a low-carbon economy, taking into account the associated national and local impacts. Our study also contributes to the literature about the evaluation framework of coal phase-out projects around the world, improving the understanding of their associated impacts beyond the case study country. [ABSTRACT FROM AUTHOR]

Measuring the performance of environmentally sustainable supply chains instead of chain constitute has become a challenge despite the convergence of the underlining principles of sustainable supply chain management. This challenge is exacerbated by the fact that supply chains are inherently dynamic and complex and also because multiple measures can be used to characterize performances. By identifying some of the critical issues in the literature regarding performance measurements, this paper contributes to the existing body of literature by adopting an environmental performance measurement approach for economic sectors. It uses economic sectors and evaluates them on a sectoral level in specific countries as well as part of the Global Value Chain based on the established multi-regional input-output (MRIO) modeling framework. The MRIO model has been used to calculate direct and indirect (that is supply chain or upstream) environmental effects such as CO 2 , SO 2 , biodiversity, water consumption and pollution to name just a few of the applications. In this paper we use MRIO analysis to calculate emissions and resource consumption intensities and footprints, direct and indirect impacts, and net emission flows between countries. These are exemplified by using carbon emissions, sulphur oxide emissions and water use in two highly polluting industries; Electricity production and Chemical industry in 33 countries, including the EU-27, Brazil, India and China, the USA, Canada and Japan from 1995 to 2009. Some of the highlights include: On average, direct carbon emissions in the electricity sector across all 27 member states of the EU was estimated to be 1368 million tons and indirect carbon emissions to be 470.7 million tons per year representing 25.6% of the EU-27 total carbon emissions related to this sector. It was also observed that from 2004, sulphur oxide emissions intensities in electricity production in India and China have remained relatively constant at about 62.8 gSO x /, respectively, $ and 84.4 gSO x /$ although being higher than in other countries. In terms of water use, the high water use intensity in China (1040.27 L/$) and India (961.63 L/$), which are among the highest in the sector in the electricity sector is exacerbated by both countries being ranked as High Water Stress Risk countries. The paper also highlights many advantages of the MRIO approach including: a 15-year time series study (which provides a measurement of environmental performance of key industries and an opportunity to assess technical and technological change during the investigated time period), a supply chain approach that provides a consistent methodological framework and accounts for all upstream supply chain environmental impacts throughout entire global supply chains. The paper also discusses the implications of the study to environmental sustainability performance measurement in terms of the level of analysis from a value chain hierarchy perspective, methodological issues, performance indicators, environmental exchanges and policy relevance. [ABSTRACT FROM AUTHOR]

In this article, we track how consumption in the United States, a highly developed 'core' country, triggers value added and carbon inequalities around the globe. We consider these two sources of inequality for all commodities and services consumed in the United States, and then for three specific sectors, these being electronics, motor vehicles, and wearing apparel. Our findings show how the production of commodities for U.S. consumption tends to reify inequalities between countries. Larger shares of value added (in comparison to shares of carbon emissions) are generally experienced by more-developed, more-integrated countries, whereas the opposite tendency is experienced in less-developed, less-integrated regions. We note how these between-country differences can depend on the product chains that are analyzed. Our article makes use of a novel combination of social network analysis and multiregional input-output analysis to better capture some intuitive ideas of global trade and its consequences. [ABSTRACT FROM AUTHOR]

Rapid economic growth and urbanization in China have led to a substantial change in consumption patterns and diet structure of Chinese consumers over the past few decades. A growing demand for feed, fuel, and fiber also places intense pressure on land resources. With continuing growth of China's economy and migration from rural to urban, the increase in food consumption and change in diet structure will likely continue, which will not only impose pressure on domestic land resources, but also exert impact on land resources in other countries through import. This article applies a global multiregion input-output (MRIO) model to trace agricultural land use along global supply chains and examines the impact of China's future food consumption on global land use in 2030 against different socioeconomic and technological scenarios. Our scenarios show that by 2030, China would need an additional 21% of cropland to support its increasing food demand, driven by population growth, urbanization, and income growth and the associated diet structure change. Almost one third of cropland associated with household consumption (34 million hectares [Mha]) will be 'outsourced' to foreign countries, such as Argentina, Brazil, the United States, and Thailand, for the consumption of cereal grains, soybeans, and paddy rice. China also consumes 2.4 Mha of cropland from Africa for its consumption of cereal grains and oil seeds. The dependence of domestic consumption on significant amounts of foreign cropland shows that China would face serious challenges to meet its grain self-sufficiency policy in the future, and, at the same time, this dependence would contribute to environmental and food security problems elsewhere. [ABSTRACT FROM AUTHOR]

The number of energy–water nexus studies has been increasing recently due to the significant linkages between energy generation and water consumption, but no study has looked at water quantity and quality impacts as well as carbon emissions associated with electricity production. Using integrated hybrid life cycle analysis, this study examines the life cycle impacts of pulverized coal, wind power and solar power on carbon dioxide (CO 2 ) emissions, water consumption and water quality in Inner Mongolia, China. Our research findings show that pulverized coal emits 1213.5 g of CO 2 per kilowatt-hour (g/kW h) of electricity output, compared with 34.4 g/kW h for wind power and 67.4 g/kW h for solar photovoltaic. Water consumption for pulverized coal, wind power and solar photovoltaic are 3.3, 0.7 and 0.9 l/kW h, respectively. The water requirement to dilute the life cycle chemical oxygen demand (COD) discharge would increase water consumption during production processes of pulverized coal, wind power and solar photovoltaic systems by 0.11, 0.09 and 0.19 l/kW h, respectively. Given that the State Grid Corporation of China aims to increase the power generation capacity that provides power supply to regions outside Inner Mongolia to 120 GW by 2020, electricity outflows could contribute 520 million tonnes of CO 2 emissions, which would be similar to the CO 2 emissions of the UK in 2010, and 1460.8 million m 3 of water. This study reveals that substantial reductions in CO 2 emissions and water consumption can be attained if the existing coal-dominated power generation was substituted by wind power in Inner Mongolia. [ABSTRACT FROM AUTHOR]

Since the mid-1990s three Baltic States have significantly increased their per capita gross domestic product (GDP) and at the same time have managed to keep the CO2 equivalent (CO2e) emissions low. We used structural decomposition analysis to identify the drivers of change for CO2e emissions in these countries between 1995 and 2009, a period that includes the collapse of the Soviet Union, restructuring and economic growth and the great recession. The results show that final demand has been the main driving force for increasing emissions in the Baltic States and would have caused an 80%, 64% and 143% emission increase in Estonia, Latvia and Lithuania, respectively, all other factors kept constant. This increase has been partly offset by a declining emission intensity of the economy, especially in Latvia and Lithuania; whereas in Estonia, which has one of the highest emission intensities in Europe, a shift in consumption patterns towards low carbon consumption items and a decarbonizing economic structure were the main balancing factors. It is likely that the Baltic States will experience a continuation of economic growth given their relatively low per capita GDP, which is less than half of the European Union average thus adequate carbon policies are paramount. [Copyright &y& Elsevier]

Highlights: [•] Peak Oil (PO) poses a potentially high risk to world economies due to its immediacy and eventual impacts. [•] US economic sectors, which are economically and structurally important and vulnerable to oil price shocks, are identified. [•] Important sectors that are vulnerable to oil price shocks may put the entire US economy at risk in the case of PO. [•] Results provide early warning to downstream companies about potential ‘trouble’ in their supply chain. [•] Our tool can inform PO policy action and help decision makers in designing a roadmap toward a post-carbon economy. [ABSTRACT FROM AUTHOR]

China faces the challenge of balancing unprecedented economic growth and environmental sustainability. Rather than a homogenous country that can be analyzed at the national level, China is a vast country with significant regional differences in physical geography, regional economy, demographics, industry structure, and household consumption patterns. There are pronounced differences between the much-developed Eastern-Coastal economic zone and the less developed Central and Western economic zones in China. Such variations lead to large regional discrepancies in carbon dioxide (CO2) emissions. Using the 28 regional input-output tables of China for 2002 and 2007 and structural decomposition analysis (SDA), we analyze how changes in population, technology, economic structure, urbanization, and household consumption patterns drive regional CO2 emissions. The results show a significant gap between the three economic zones in terms of CO2 emission intensity, as the Eastern-Coastal zone possesses more advanced production technologies compared to the Central and Western zones. The most polluting sectors and largest companies are state-owned enterprises and thus are potentially able to speed up knowledge transfer between companies and regions. The 'greening' of the more developed areas is not only a result of superior technology, but also of externalizing production and pollution to the poorer regions in China. The results also show that urbanization and associated income and lifestyle changes were important driving forces for the growth of CO2 emissions in most regions in China. Therefore, focusing on technology and efficiency alone is not sufficient to curb regional CO2 emissions. [ABSTRACT FROM AUTHOR]

Abstract: The Yellow River, the second longest river in China, is facing increasing water scarcity due to rising water consumption of a fast growing economy and an increasingly urbanized population with water-intensive consumption patterns. The Yellow River Basin (YRB) is divided into three regions: the upper, middle and lower reaches; each with very different characteristics in terms of water resources, economic structure and household income and consumption patterns. Virtual water has been recognised as a potentially useful concept for redistributing water from water-rich to water-poor regions. In this study, we develop a Multi-Regional Input–Output model (MRIO) to assess the regional virtual water flows between the three reaches of the basin and the rest of China distinguishing green and blue water, as well as rural and urban household water footprints. Results show that all three reaches are net virtual water exporter, i.e. production and consumption activities outside the basin also put pressure on the water resources in the YRB. The results suggest a reduction of the export of virtual blue water that could instead be used for producing higher value added but lower water-intensive goods. In particular, the lower reach as the most water scarce region in the basin should increase the import of water intensive goods, such as irrigated crops and processed food products, from other more water abundant regions such as the South of China. Thus, trading virtual water can help sustain the economic growth of the regions within the basin thus easing the pressure from water shortage. In addition, there is a huge gap between urban and rural household water footprints in the basin. The average urban household’s water footprint is more than double the water footprint of a rural household in the basin. This is due to the higher urban household consumption of water-intensive goods and services, such as processed food products, wearing apparel and footwear, hotel and catering services and electricity. [Copyright &y& Elsevier]

The water footprint has been introduced as a potential sustainability indicator for human-induced water consumption, and has frequently been studied at local, national and international scales during the last decade. While water footprints are sometimes understood as a measure that includes environmental impact assessment, the water footprint as used in this paper refers to volumes of water consumed, without including weighting procedures to allow for the assessment of impacts. Two types of approaches have been applied to calculate the water footprint in the literature: bottom-up and top-down approaches. This study compares and discusses advantages and limitations of the water footprint of nations based on two input–output top-down approaches (Water Embodied in Bilateral Trade (WEBT) and Multi-regional Input–Output Analysis (MRIO)) and of the existing national water footprint accounts from the literature based on the bottom-up approach. The differences in the bottom-up and WEBT approaches are caused by inter-sectoral cut-off, because bottom-up approaches do not consider the entire industrial supply chains, while the WEBT method covers the water footprint by tracing the whole domestic supply chain of each country. The differences in the WEBT and MRIO approaches are due to an inter-regional cut-off effect, as the WEBT approach only traces domestic supply chains whereas the MRIO approach traces entire global supply chains. We found that both bottom-up and top-down approaches are heavily dependent on the quality of existing datasets, and differ substantially. The total water footprints of nations based on different approaches vary by up to 48%, and this variation is even larger at the sector level. [ABSTRACT FROM PUBLISHER]

Household carbon emissions are mainly affected by income and other key demographic factors. Understanding the contribution of these factors can inform climate responsibilities and potential demand-side climate mitigation strategies. By linking US consumer expenditure survey data with a nested national within a global multi-regional input-output model, this study estimates consumption-based GHG emissions for 9 income groups and assesses the carbon inequality in the US for 2015. Our results show that the per capita carbon footprint (CF) of the highest income group (>200 thousand USD per year) with 32.3 tons is about 2.6 times the per capita CF of the lowest income group (<15 thousand USD) with 12.3 tons. This is due to large gap in consumption volume and associated carbon emissions along the entire global production chain. Consumption pattern tends to narrow the gap in household per capita CF between income groups due to the lower carbon intensity per dollar spent by higher income groups. Another important factor influencing carbon footprints is household size and thus sharing of household equipment and other consumption items. The US average per capita CF is 18.1 tons compared to the global average of approximately 5 tons. The high carbon footprint across income groups in the US is largely due to the large contribution of emissions from heating and cooling and private transport, which reflects the settlement structure and lifestyles in the US, relying heavily on cars and living in larger houses. [ABSTRACT FROM AUTHOR]

In order to combat environmental pollution, China enacted the Environmental Protection Tax Law in early 2018. Yet the impacts of the environmental tax on individual regions with different socioeconomic statuses, which are crucial for social justice and public acceptance, remain unclear. Based on a Multi-Regional Input-Output (MRIO) table and a nationally regulated tax payment calculation method, this study analyzes the distributional impacts of an environmental tax based upon province's consumption from both inter-provincial and rural-urban aspects. The national tax revenue based on the current levy mechanism is estimated to be only one seventh of the economic loss from premature mortality caused by ambient particulate matter (PM 2.5). The taxation may slightly alleviate urban-rural inequality but may not be helpful with reducing inter-provincial inequality. We further analyze two alternative levy mechanisms. If each province imposes taxes to products it consumes (rather than produces, as in the current mechanism), with the tax rate linearly dependent on its per capita consumption expenditure, this would moderately increase the national tax revenue and significantly reduce inter-provincial inequality. To better compensate for the economic costs of air pollution and reduce regional inequality, it would be beneficial to increase the tax rate nationwide and implement a levy mechanism based on provincially differentiated levels of consumption and economic status. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emissions in the U.S. peaked and declined in the first decade of the 21st century, largely attributed to the increased use of natural gas and renewable energy replacing coal. However, if and to what extent household consumption also played a role in this trend is still debated. Finding demand-side options is necessary to hedge against the risks of technology solutions failing to materialize. To fill this gap, this study analyzes the change in GHG emissions driven by U.S. household consumption, explores the drivers of this change and the contribution of different income groups. To this end, this study combined the U.S. consumer expenditure survey with an environmentally-extended multi-regional input-output framework to analyze changes in GHG emissions induced by household consumption between 2001 and 2015. This study further analyzed how much population, consumption volume and consumption patterns drove emission changes by quintile income groups. The results show that changes in household consumption contributed approximately one-third of the national emission decline. The decline in GHG emissions from U.S. households was mainly associated with a decrease in the consumption of carbon-intensive products, including gasoline, electricity, and animal-based food products. The top quintile income households were the main contributors to the emission increase before the peak, while the third and fourth income quintiles became emission mitigation leaders after 2010. Carbon inequality increased during the 2001–2006 period, mainly driven by increased wealth and consumption of high-income households, and was relatively stable after the peak. Emissions from certain consumption categories of the top quintile group are significantly higher than the bottom four quintiles with increasing trends, especially leisure-related services and goods, which require more attention in future policymaking for emission reduction. • U.S. household consumption contributed approximately one-third to the national GHG emission decline. • Top quintile income households were primary contributors that drove up GHG emissions before 2007. • The change in consumption pattern was the major contributor to emission decline from a household consumption perspective. • Carbon inequality is positively associated with household-driven GHG emissions. [ABSTRACT FROM AUTHOR]

The concept of the water footprint has been recently introduced as an important indicator for human-induced water consumption. The water footprint is defined as the total volume of water used during production and consumption of goods and services as well as direct water consumption by humans. Water is not only consumed directly but also indirectly in production processes. Therefore, calculating the water footprint enables us to quantify total water consumed along the whole global supply chain. In this paper, we develop a regional input–output (IO) model extended by water consumption coefficients to quantify the respective domestic water footprint for different consumption categories for the South-East and North-East of England and the UK, i.e. the water consumed directly and indirectly along the regional supply chain. In addition, we calculate the total water footprints which include both domestic water consumption and the water required in other countries to produce goods and services imported and consumed in the region under investigation through applying a multi-regional input–output (MRIO) model. Both footprints also include households'' direct consumption of water. With regards to the two regions, we can observe a very pronounced regional disparity of regional (domestic and total) water footprints between the relatively water-scarce South-East and the water-rich North-East of England. We find that the domestic water footprint per capita in the South-East is 22% higher than the domestic water footprint per capita in the North-East. The key water consumers include Agriculture, Food Products, Electricity and Gas Production, and Hotel and Catering. The total water footprints per capita in the South-East (1257m3/year) are more than twice the ones in the North-East (597m3/year). The domestic water footprint focuses only on the supply chain effects and associated water consumption within the regional boundaries, which are usually of higher interest to policy makers and water companies concerned with the balance of supply and demand of water resources within their respective administrative boundaries or watersheds. The total water footprint allows assessing global effects and supports global supply chain management and is also introducing notions of fairness and equity in terms of resource consumption. [Copyright &y& Elsevier]

Investment makes an outstanding contribution to the global economy while significantly impacting on global carbon emissions. However, few attempts have been made to analyze temporal changes in historical emissions induced by investment, and it is difficult to determine which countries are responsible for emissions reductions. Here we investigate the evolution in the carbon emissions embodied in investment (ECI) at global and national levels with the Global Multi-regional input-output (GMRIO) model, aiming to address the question of "Who should be responsible for how much, when it comes to emissions reductions?". Our results show that global ECI increased by 72.4% from 1990 to 2021, with intermediate input structure being the key driver. Specifically, China, the United States and India had the highest ECI, and domestic investment level was responsible for promoting the growth of investment-related emissions. Improvements in emission intensity were the primary contributor to reductions. The construction, electrical and machinery, and transport equipment sectors were the leading sectors in shaping national investment-related emissions. To enable more effective reduction policies measures of ECI reduction, serious consideration should be given to technology cooperation and sharing. • The evolutions and factors of the carbon emissions embodied in investment (ECI) are investigated. • Global ECI increased by 72.4% in 1990–2021, and grew as a share of total emissions. • Intermediate input structure is the key factor, while emission intensity is the primary dedicator. • The construction and electrical and machinery sectors played leading roles in shaping national ECI. [ABSTRACT FROM AUTHOR]

• Provincial CO 2 emissions of China are investigated from different perspectives. • Embodied emission flows driven by final demands and primary inputs are quantified. • Income-based emissions are relatively higher in energy resource-abundant province. • Tertiary industries are the major contributors to China's income-based emissions. Emission accounting can help to identify main CO 2 emitters and inform emission mitigation policymaking. Previous studies have proved that the application of different accounting principles results in different emission levels, thus bring different policy implications, while the emissions enabled by primary inputs (or income-based emission) have been overlooked in studies for carbon mitigation in China. Understanding the role of primary inputs in CO 2 emissions is a prerequisite to create efficient supply-side mitigation policies. Here, we conduct a quantitative study of China's provincial production-, consumption-, and income-based CO 2 emissions in a unified multi-regional input-output analysis framework. The results are compared from the three perspectives for 30 provinces in China to help the government identify the main policy targets from production, demand, and supply sides. We found that 64% and 35% of China's emissions are transferred among provinces driven by final demands and primary inputs, respectively. Mitigation policies in heavily industrialized provinces, such as Hebei, Liaoning, and Henan, where the production-based emissions are higher than the consumption- and income-based emissions, should be focused on production side. Similarly, policies in eastern coastal developed provinces and resource-abundant provinces should be focused on demand- and supply-side, respectively. Moreover, we found that tertiary industries, which previous studies generally regard as low-carbon industries, are the major contributors to China's income-based CO 2 emissions with a total of 2026 Mt or 31% of China's total income-based CO 2 emissions. Thus, expanding tertiary industries without reducing their industrial linkages to carbon-intensive industries is not conducive to China's emission reduction. [ABSTRACT FROM AUTHOR]

Abstract Currently, over 20% of global electricity and 30% of global CO 2 emissions from fuel combustion are generated in China. Understanding the driving forces of CO 2 emissions from power generation is critical for both decarbonizing the power sector and achieving national carbon reduction targets. The objectives of this study were to identify critical driving forces behind changes in CO 2 emissions from the power sector and to propose appropriate decarbonization pathways. First, the generation and demand structures of the power sector were introduced into a CO 2 emission accounting model and decomposition analysis. Instead of traditional input–output analysis, structural decomposition analysis modified using a power transmission table was used to investigate the impacts of five driving factors of CO 2 emissions from China's power generation. The five driving factors comprised the proportion of thermal power, power generation technology, power generation structure, power demand structure and power demand, whereby the latter was divided further into nine detailed parts. Considering five regional power grids in China, the contributions of these factors were analyzed at both national and regional level. The results showed that the majority of the increase in CO 2 emissions during 2007–2012 could be attributed to electricity generation (96.2%) driven by changes in power demand, which should be the key to power sector decarbonization. By contrast, 30.7% of emissions were offset by changes in the proportion of thermal power and technology, demonstrating the obvious effects of China's policy on clean energy transition. Additionally, all power grids exhibited an increase in CO 2 emissions from electricity generation, with the east and central grids accounting for 64% of the national increase. Power transmission structure had only a small impact on CO 2 emissions from power generation. By using the electricity transmission table, we modified SDA to overcome the time lag issues and eliminate the reliance on IO data, and continuous annual data rather than aggregated five-yearly data can be used to capture the structural effects, thus providing more precise results for the driving forces of emission changes. Our case study shows that there is huge potential in extending the IO-based SDA method to other trade-related studies. Highlights • A new electric CO 2 emission decomposition model is proposed. • Drivers of CO 2 emissions from power demand in five grids of China are investigated. • Power transmission structure effects on CO 2 emissions are presented. [ABSTRACT FROM AUTHOR]

Abstract There exist substantial differences in top-of-atmosphere direct radiative forcing of aerosols due to a region's economic production (RF p) and consumption (RF c), in the context of economic globalization, trade and globalizing air pollution. Yet an explicit systematic analysis of all socioeconomic and atmospheric factors determining the RF difference is lacking. Here, we evaluate five socioeconomic (population, per capita output, emission intensity) and atmospheric (chemical efficiency and radiative efficiency) factors that determine a region's RF p , RF c and their difference. We consider the RF of secondary inorganic aerosols, primary organic aerosols and black carbon by 10 regions worldwide in 2007. The population size varies by a factor of nine across the regions, and per capita output by 40 times from both production- and consumption-based perspectives. The cross-regional spread reaches a factor of 181 (species dependent) for production-based emission intensity and a factor of 96 for consumption-based intensity. From one region to another, production-based chemical efficiency changes within a factor of 5 and consumption-based efficiency within a factor of 3.5. Radiative efficiency varies slightly across the regions (within 2) from both production- and consumption-based perspectives. Although socioeconomic factors are often a greater driver for the difference between a source region's RF p and RF c , the atmospheric factors are also important for many source regions and species. Our results contribute to regional attribution of climate change and establishment of effective international collaborative mitigation strategies. Highlights • Multiple factors differentiate a region's aerosol RF c from its RF p. • Socioeconomic factors usually play a greater role for most regions and species. • Atmospheric factors are also important for some regions and species. • Our study is relevant to regional attribution of aerosol radiative forcing. [ABSTRACT FROM AUTHOR]

The first commitment period of the Kyoto Protocol came to an end in 2012 and more developing countries began to participate in the new phase of world carbon emission reduction. Kazakhstan is an important energy export country and a pivot of the "Belt and Road Initiative" (BRI). Despite its emissions are relatively small compared with huge emitters such as China and the US, Kazakhstan also faces great pressure in terms of CO 2 emission reduction and green development. Accurately accounting CO 2 emissions in Kazakhstan from both production and consumption perspectives is the first step for further emissions control actions. This paper constructs production-based CO 2 emission inventories for Kazakhstan from 2012 to 2016, and then further analyses the demand-driven emissions within the domestic market and international trade (exports and imports) using environmentally extended input-output analysis. The production-based inventory includes 43 energy products and 30 sectors to provide detailed data for CO 2 emissions in Kazakhstan. The consumption-based accounting results showed that certain sectors like construction drive more emissions and that the fuel consumption in different sectors varies. Furthermore, Russia and China are major consumers of Kazakhstan's energy and associated emissions, with the construction sector playing the most important role in it. The results suggested that both technology and policy actions should be taken into account to reduce CO 2 emissions and that the BRI is also a good chance for Kazakhstan to develop a "Green Economy". • CO 2 emission inventories are estimated in Kazakhstan from 2012 to 2016. • Consumption-based emissions patterns are different from production-based ones. • Construction drives most emissions embodied in trade. • Kazakhstan should develop renewable energy to achieve the "Green Economy". [ABSTRACT FROM AUTHOR]